Consciousness may be explained by multiple, partly compatible theories rather than a single winner. A group of scientists representing different theories argue that various accounts often address different aspects or mechanistic levels of conscious experience, so they do not necessarily contradict each other. Instead, several theories may converge on fundamental neuronal mechanisms and be complementary, allowing multiple perspectives to simultaneously advance understanding. The authors advocate for unifying, integration-oriented approaches that combine valuable elements from diverse theories, an approach that has so far been largely neglected.
Simulating a simple computation in an artificial neural network, researchers recorded neuron activity during visual stimulation and replayed those signals back into the same neurons. This replay degraded the computation by erasing counterfactual activity patterns—alternative neural states that could have occurred—while leaving ongoing brain activity unchanged. This outcome reveals a disconnect between neural activity and computational structure, challenging the computational functionalist view that consciousness emerges from the right computations, whether in machines or biological brains.
Large language models are unlikely to become conscious because they lack three key features of biological consciousness. First, they do not receive the embodied, real-world sensory information that grounds human experience. Second, their architectures miss essential neural structures of the mammalian thalamocortical system linked to awareness. Third, the evolutionary and developmental processes that produced conscious living organisms—rooted in survival-driven action and multi-level cellular processes—have no counterpart in current artificial systems.
Integrated information, a proposed signature of consciousness, is maximized in a biophysical network model when the nonspecific thalamus drives thick-tufted layer 5 pyramidal neurons into a regime of time-varying synchronous bursting. In this regime, variable spiking dynamics with broad pairwise correlations support enhanced integrated information. The peak in integrated information coincides with criticality signatures and empirically observed layer 5 pyramidal bursting rates. These findings suggest that the thalamocortical core of the mammalian brain may be evolutionarily configured to optimize effective information processing, offering a potential neuronal mechanism linking microscale theories to macroscale signatures of consciousness.